Investigators developed and validated a masked autoencoder deep learning model using vision transformer technology to automate the detection and grading of nuclear cataracts from slit-lamp images.

Abstract: Computed tomography (CT) is extensively used for accurate visualization and segmentation of organs and lesions. While deep learning models such as convolutional neural networks (CNNs) and ...

Abstract: Medical portable devices are increasingly requiring high accuracy, speed, and low inference jitter to meet the urgent demands of healthcare. Modern hybrid attention-based segmentation ...